onboarding: are online and offline data getting married? · 2015-03-02 · acme loyalty member ken...

Onboarding: Are Online and

Offline Data Getting Married?

IAPP GLOBAL PRIVACY SUMMIT

MARCH 5, 2015

Sheila Colclasure, Acxiom

Noga Rosenthal, NAI

Ken Dreifach, ZwillGen PLLC

State of the Market History of Data and Privacy

• Top of Mind for Decades • Active collection • Consent based uses • PII and Aggregate • Batch enabled • Industry way ahead of regulation

Big Data = Big Changes • Volume, Velocity, Variety and Analytics • PII, DII, Pseudo-anonymous, De-identified • Passive vs active collection and sharing • Definition of “sensitive data” evolving and new harms • Offline to Online = Connection

Need to reach Audiences Digitally

How Does Onboarding Work?

3

CRM Data

Ken at One Main St. = Acme Loyalty Member

Ken = [email protected]

= HASH of [email protected]

Ken appears online. Cookie is placed on Ken’s browser with

Acme CRM data.

Cookie is redirected to Acme’s DMP.

Acme sends Ken an ad for new Acme widgets.

Offline Analytics

mailto:[email protected]



4

CRM Data





Acme CRM data.



Offline Analytics




5

CRM Data





Acme CRM data.



Offline Analytics




6

CRM Data





Acme CRM data.



Offline Analytics




7

CRM Data





Acme CRM data.



Offline Analytics




8

CRM Data





Acme CRM data.



Offline Analytics



PII vs. Anonymous - Definitions

Device Identifiable Information

Anonymous

Choice

X

De-Identified Information

X Personally Identifiable Information

Aggregate Information

Pseudo- anonymous

/ /

Personal Pseudo-

anonymous

PII DII AGI De-ID

SANI

ANI PII SANI

Covered Information

Ease of Technical Re-identification 100% 0%

What is Hashing?

10

[email protected] Email run through Algorithm

43307bb5a669b247270a4d81cce6f3ff


56699cc2f770d026374e2e9eccl925tg


765fh9ku40ldne2f302mjnf983yyh76h


12h7ufko0epmn678hfy549ldmn9853kl

Use of Hashing for Onboarding

11

Email run through Algorithm

43307bb5a669b247270a4d81cce6f3ff

Email run through Algorithm

56699cc2f770d026374e2e9eccl925tg

765fh9ku40ldne2f302mjnf983yyh76h

12h7ufko0epmn678hfy549ldmn9853kl

[email protected]

[email protected]

[email protected]

[email protected]

[email protected]

[email protected] [email protected]

[email protected]

Privacy Framework for Onboarding

Ecosystem

Best Practices

Data

Best Practices

ONLINE OFFLINE

How Does Onboarding Enable Marketing?

• Did (hashed) Ken see the Acme ad?

• Did (aggregated) Ken buy an Acme product?

• Can/should we send (anonymous) Ken another ad?

• Or did Ken opt-out (of all ads)?

• What other consumers look like Ken (“lookalike” modeling)? • Based on offline, demographic, transactional

data?

13

Summary of Privacy Protections

• Reliable Sources: Notice At Point of Data Collection • Notice: Ensure that users are provided appropriate

notice concerning the collection and use of data for Interest-Based Advertising: • at the “match point” website sending hashed data • on the onboarding partner’s site (e.g, NAI member).

• Choice: Opt-Out • Non-association of non-PII with PII • Use of Hash Scripts

• No passage of (readable) PII from publisher

• Contractual enforcement

14

Non-Merger of PII + Non-PII

15

CRM Data





Acme CRM data.



Offline Analytics



Non-Merger of PII + Non-PII

16

[email protected]

= HASH

TRIGGER

No Data Merge

Ken appears online. Cookie is placed on Ken’s

browser with Acme CRM data.


Avoid Re-identification

17

CRM Data





Acme CRM data.



Offline Analytics



Avoid Re-identification

18

Acme Ad to Ken for Widget

Match back to Offline

Behavior/PII

No OBA Data

Online-Offline Marriage: Backstory . . .

19

NOVEMBER 1999

Forward to 2015: NAI Code

The 2013 NAI Code defines Interest-Based Advertising (“IBA”) as

“the collection of data across web domains owned or operated by different entities for the purpose of delivering advertising based on preferences or interests known or inferred from the data collected.”

This provision covers data that is collected on one domain for use on another domain owned or operated by another entity for the purpose of delivering advertising based on known or inferred preferences.

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Onboarding Notice & Choice

NOTICE Access to Integrated Online Notice & Choice Platforms

• Notice via Match Partner sites

• Notice via DAA/NAI Sites: Ubiquitous “Enhanced” Notice

CHOICE Multi-channel Opt-Out (NAI, DAA)

• Linked from Match Partner Sites

• Linked from Trillions of Ads Each Month

DAA AboutAds.info

Opt-Out Channel: NAI Opt-Out Page

23

Onboarding Opt-Out Permanence

24

Onboarded Data: Reliable Sources Rule

25

Strict Rules For

“Sensitive” Data

(NAI Code)

Sexual Orientation

Precise, Serious Health Condition

Sensitive Data Evolving: New Harms

Historically Sensitive Commercial Data » Identification, Financial. Medical, Children

•New Categories of Sensitive Commercial Data

» Precise geo-location

» At-risk populations (children & elderly) » Teens – 0-12, 13-17

» Elderly = over 60

» Social network information (public & non-public)

» Biometrics & Facial recognition

» Modeled Data

Traditional Harm » Financial, Physical

New Harms » Social Harms, Emotional, Reputational

Finances

Identification

Medical

Social Networks

Biometrics

At Risk Populations

Facial Recognition

Location

Onboarded Data: Reliable Sources Rule

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Follow Other

Data Rules!

Voter Registration Data

Kids’ Data

Credit Data

HIPAA

VPPA

Privacy Policies + “Reliable Sources”

Data Rules: How “Sensitive” is Too Sensitive?

28

EU vs. US

• EU Sensitive Data = Political, Ethnicity, Religion, Race, Sex Life, Health,

• US Sensitive Data = “Sensitive” per NAI

• FTC and U.S. Senate Commerce Committee Data Broker Report (Dec. 2013, May 2014)

Questions?

29

onboarding: are online and offline data getting married? · 2015-03-02 · acme loyalty member ken...

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